Journal of Applied Optics, Volume. 43, Issue 3, 444(2022)
Improved ViBe algorithm based on adaptive threshold and dynamic update factor
Figures & Tables(6)
Fig. 1. Comparison images of target detection effects in ViBe algorithm with different background modeling algorithms
Fig. 2. Comparison images of target detection effects in ViBe algorithm with different foreground and background judgment thresholds
Fig. 3. Comparison images of target detection effects in ViBe algorithm with different background update factors
Fig. 5. Comparison images of target detection effects of four algorithms in six types of scenes
Table 1. Average values of test indexes of four algorithms in six types of scenes
View tableView in ArticleTable 1. Average values of test indexes of four algorithms in six types of scenes
算法 Rprecision Rrecall PPWC F RFPR RFNR KDE 0.702626667 0.506002 3.4639 0.548503 0.015443 0.493998 GMM 0.6513 0.362367 3.3073 0.446828 0.006733 0.637633 VIBE 0.757776667 0.567875 2.7843 0.639273 0.009717 0.432125 本文算法 0.916511667 0.604228 1.9648 0.720945 0.00253 0.395772
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Wei CHEN, Yu LIU, Hongtao LI, Jing SUN, Ning YAN. Improved ViBe algorithm based on adaptive threshold and dynamic update factor[J]. Journal of Applied Optics, 2022, 43(3): 444
Paper Information
Category: OE INFORMATION ACQUISITION AND PROCESSING
Received: Oct. 18, 2021
Accepted: --
Published Online: Jun. 7, 2022
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